1 citations · 2 across the 4 of their papers we have counts for
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FiRe: Fixed-Noise Refinement for Visual Counterfactual Explanations
Yan Zeng, Changlu Guo, Oskar Kristoffersen +3
Visual counterfactual explanations aim to change classifier decisions through realistic and localized edits while preserving decision-irrelevant content. Existing DDPM-based method…
Materialist: Physically Based Editing Using Single-Image Inverse Rendering
Lezhong Wang, Duc Minh Tran, Ruiqi Cui +5
Achieving physically consistent image editing remains a significant challenge in computer vision. Existing image editing methods typically rely on neural networks, which struggle t…
MaskDiME: Adaptive Masked Diffusion for Precise and Efficient Visual Counterfactual Explanations
Changlu Guo, Anders Nymark Christensen, Anders Bjorholm Dahl +1
Visual counterfactual explanations aim to reveal the minimal semantic modifications that can alter a model's prediction, providing causal and interpretable insights into deep neura…
MozzaVID: Mozzarella Volumetric Image Dataset
Pawel Tomasz Pieta, Peter Winkel Rasmussen, Anders Bjorholm Dahl +4
Influenced by the complexity of volumetric imaging, there is a shortage of established datasets useful for benchmarking volumetric deep-learning models. As a consequence, new and e…
SA-UNetv2: Rethinking Spatial Attention U-Net for Retinal Vessel Segmentation
Changlu Guo, Anders Nymark Christensen, Anders Bjorholm Dahl +2
Retinal vessel segmentation is essential for early diagnosis of diseases such as diabetic retinopathy, hypertension, and neurodegenerative disorders. Although SA-UNet introduces sp…
Fast Sphericity and Roundness approximation in 2D and 3D using Local Thickness
Pawel Tomasz Pieta, Peter Winkel Rasumssen, Anders Bjorholm Dahl +1
Sphericity and roundness are fundamental measures used for assessing object uniformity in 2D and 3D images. However, using their strict definition makes computation costly. As both…